inMotion

Dataset Labels:

A - Inside the Bus

B - Outside the Bus

Route Labels:

LoopA - Inside of the bus

LoopB - Outside of the bus

AB - From inside to outside the bus

BA - From outside to inside the bus

Dataset Structure:

Each line represents a sequence of RSSI measurements captured every second over 10 seconds, associated with a MAC address and a label indicating the route taken.

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Dataset Example

MAC Address	1	2	3	4	5	6	7	8	9	10	Trajeto
e6:53:5c:2a:e8:e2	-48.0	-48.0	-54.0	-53.0	-55.0	-50.0	-57.0	-53.0	-55.0	-51.0	LoopB
e6:53:5c:2a:e8:e2	-41.0	-31.0	-31.0	-35.0	-40.0	-48.0	-45.0	-48.0	-54.0	-56.0	AB

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SCHEMA:

How to use the export.py script:

# take so many groups as you want
 uv run export.py \                         
  --input wavecom_files/noiseG1BtoA_G2loopB.txt  \
  --output data/noiseBA_BB.csv \
  --group G1:ea:51:ae:7f:62:fa,76:64:61:f6:e6:14 \ # it can take N MACs
  --group G2:e6:53:5c:2a:e8:e2,04:b1:67:ac:8d:65 \ # it can take N MACs
  --group-label G1:BA \ # each group have a label
  --group-label G2:LoopB \ # each group have a label

Arguments:

--input: Input wavecom data file --output: Output CSV file --group: Group definition in the form label:mac1,mac2,... (repeatable) --group-label: Map group name to final label, e.g., G1:AB (repeatable)

How to use the merge_csv.py script:

python merge_csv.py --input data/ --output dataset.csv

uv run export.py \
--input wavecom_files/noiseG1AtoB_G2BtoA2.txt
--output data/noiseAB_BA.csv
--group G1:2e:ad:62:53:35:66,76:64:61:f6:e6:14 \ # it can take N MACs --group G2:e6:53:5c:2a:e8:e2,04:b1:67:ac:8d:65 \ # it can take N MACs --group-label G1:AB \ # each group have a label --group-label G2:BA \ # each group have a label

uv run export.py --input wavecom_files/noiseG1AtoB_G2BtoA2.txt --output data/noiseAB_BA2.csv --group G1:2e:ad:62:53:35:66,76:64:61:f6:e6:14 --group G2:e6:53:5c:2a:e8:e2,04:b1:67:ac:8d:65 --group-label G1:AB --group-label G2:BA